Medical out-of-pocket spending (MOOPS), i.e. direct patient spending on medical care, can overwhelm household resources, compromise families? financial wellbeing, and engender further stress and ill health. A long-standing literature has focused on MOOPS financial burden- a prevalent measure of MOOPS relative to a disposable income threshold. Recent theoretical work, however, has drawn attention to financial risk- a distinct concept that captures the uncertain timing and magnitude of MOOPS relative to changes in individuals? health status and fluctuations in family resources. Empirical measurement of financial risk, however, remains elusive and, to our knowledge, is yet to be successfully implemented. Further, financial risk is intimately tied to household financial anxiety and precautionary behaviors- the very objects of insurance policy. While the Affordable Care Act (ACA) has reduced financial burden, the law?s effects on financial wellbeing remain less well understood, especially effects of Marketplace coverage. Because the timing and magnitude of MOOPS under Marketplace coverage depend on the premium and cost-sharing schemes variably subsidized across local insurance markets, measurement of financial risk, rather than burden, could uniquely unravel nuanced effects of Marketplace plans on financial wellbeing. Leveraging novel data construction and linkages, we will: (1) Develop theoretically-grounded prospective measures of financial risk as the 12-month incidence of catastrophic and impoverishing MOOPS, and compare them with traditional burden measures. We will construct a hierarchical monthly dataset of individual/family characteristics and healthcare events from the Medical Expenditure Panel Survey (2000-2016), linked to baseline data from the National Health Interview Survey (1998-2014) and historical thresholds of the Supplemental Poverty Measure. Using time-to-event methods, we will analyze trends (2000-2016) of both our financial risk and traditional burden measures in the adult population overall, and by key subgroups. These analyses will (a) inform how best to measure financial wellbeing, especially for differentiating protective potential of alternative insurance policy designs; (b) contrast value judgments in traditional vs. proposed measures; and (c) provide concrete methodology for monitoring of financial risk using public-use data, which is especially timely in this highly uncertain, post-reform era. (2) Estimate quasi-experimental effects of ACA Marketplace coverage and Medicaid expansions on financial risk. We will link our monthly dataset (2010-2016) to county-level uninsurance rates (2009-2013), and to health-plan data from the HIX Compare Project (2014-2016). These linkages will enable us to identify ACA effects using a rigorous difference-in-difference-in-differences design, and to capture more granular, policy- relevant effects of cost-sharing reduction and premium subsidies available in local (county) insurance markets.